"Multi-agent AI systems for collaborative code development" matching MCP servers:

An AI-powered code review agent that leverages Model Context Protocol (MCP) and Claude to provide intelligent, context-aware code reviews.

MCP server for AI-native L1 support: triages tickets, answers from a knowledge base, escalates to L2 via Telegram/GitHub, and manages feedback, with a LangGraph workflow and safety guardrails.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

Integrates GitHub repository management and local file system access to enable AI agents to perform code reviews and manage pull requests. It provides tools for listing repositories, retrieving PR diffs, and searching or reading files within a specified workspace.

An experimental MCP server that enables AI assistants to interact with VS Code workspaces through file operations, code execution, and Git management. It also provides tools for Docker integration, project scaffolding, and secure command execution using project-specific configurations.

A comprehensive MCP server that provides AI assistants with tools for file system management, Git integration, and shell command execution. It features specialized code utilities for analysis, formatting, and linting to enhance development workflows within Claude Desktop.

Provides comprehensive git tooling via MCP, including status, diffs, commits, branches, stashes, and multi-root inventory, enabling AI agents to manage repositories.

An MCP server that integrates AI assistants like Claude with GitLab's merge requests, allowing them to review code changes, add comments, and approve/unapprove merge requests directly through the GitLab API.

Enables MCP-connected AI agents to review GitHub pull requests and post meaningful inline review comments directly on them through natural language prompts.

Deterministic code review MCP server that provides tools for file selection, rule matching, comment positioning, and reflection, ensuring stable review quality without LLM calls.

Enables comprehensive GitHub PR reviews through Cursor's AI by fetching PR diffs, running static analysis tools (ESLint, Prettier, TypeScript, Semgrep), executing tests, and generating detailed code review reports with inline comments.

Enables Claude AI to run terminal commands, perform file operations, and manage git in a project directory via the Model Context Protocol.

Safe local MCP server for Windows to list, read, search, patch, backup, and verify code files in allowed folders, with Git integration and dry-run diffs.

Enables interactive GitHub pull-request review from Claude Code, with tools to fetch PRs, inspect files and repo structure, post review comments, and query a RAG index of the codebase.

A modular server that implements the Model Context Protocol standard, providing tools for interacting with GitHub, GitLab, Google Maps, Memory storage, and web automation through a unified gateway.

An MCP server for automated code review of GitHub pull requests. It checks security, quality, and license issues, and provides tools to list, inspect, and review PRs.

Tracks the complete lineage and DNA of every line of code, enabling impact analysis, bug risk prediction, and code archaeology through deterministic analysis of git history and AST.

MCP server that gives AI agents deep code understanding across multiple git repositories, combining git lifecycle management, Zoekt-based trigram code search, and cross-repo dependency analysis.

Enables coding agents to generate question-scoped repository maps, inspect symbols and SQL lineage, and audit working-tree diffs for ripple candidates, all verified against the current Git commit.

Provides local codebase intelligence as an MCP server, enabling AI agents to query dependencies, assess change impact, and produce tamper-evident change evidence packets.